Using Immunization Data Systems to Track Zero-Dose Children in Bangladesh: Mixed Methods Exploratory Study

Background Zero-dose (ZD) children—those who receive no routine vaccines—remain highly vulnerable, with global evidence showing that they are concentrated in marginalized and hard-to-reach settings. In Bangladesh, stagnant full-immunization coverage, population mobility, and inconsistencies in administrative data complicate accurate estimation of ZD and underimmunized children. Gaps in the completeness, timeliness, and accuracy of routine Expanded Programme on Immunization (EPI) information systems further limit the ability to identify and target these populations. Objective This study aimed to assess the completeness, timeliness, and accuracy of Bangladesh’s immunization data systems and to identify challenges and strategies for integrating ZD analysis into routine EPI information systems. Methods We used a mixed methods exploratory descriptive qualitative approach comprising a desk review and stakeholder interviews conducted from February 2024 to April 2024. The desk review assessed program documents, gray literature, and published studies to map routine immunization data sources and their relevance for ZD analysis. Thirteen purposively selected stakeholders, including EPI and District Health Information Software 2 (DHIS2) managers, were interviewed using semistructured interview guides to gather insights on data availability, reporting practices, and system challenges. Information from both steps was synthesized using a structured checklist to evaluate completeness, timeliness, accuracy, and feasibility of ZD tracking across data sources. Data were analyzed manually using a deductive thematic approach. Results Ten routine immunization data sources were identified, with DHIS2, the Rapid Convenience Monitoring (RCM) tool, and the EPI Coverage Evaluation Survey (CES) emerging as the primary systems for ZD tracking. Although most sources captured child-level data, the use of unique identifiers and household-level variables was inconsistent. Data quality and timeliness varied: DHIS2 faced denominator inaccuracies, CES and Bangladesh Demographic and Health Survey (BDHS) provided high-quality survey estimates, and RCM delivered real-time data from hard-to-reach areas. Multiple systems supported ZD identification, although each had limitations related to data completeness, sampling, geographic granularity, or operational constraints. Conclusions Immunization data systems in Bangladesh are fragmented, with limited ZD tracking and predominantly district-level reporting. DHIS2, RCM, and Health and Demographic Surveillance System (HDSS) are the most promising platforms for routine ZD monitoring, offering nationwide integration, real-time field data, and detailed local analysis. Harmonizing these systems and combining data from multiple sources can improve targeted interventions, subnational monitoring, and equitable vaccine coverage.